Statistics is an interdisciplinary major that draws upon faculty and courses in the departments of Computer and Information Sciences and Mathematics. The major is administered by a committee of representatives from both departments. This joint major allows students to pursue an interest in mathematical statistics, applied statistics, and related areas including biostatistics, operations research, and data mining.

Joint Minor in Statistics from MATH and CISC Departments

This joint minor allows students to pursue an interest in mathematical statistics, applied statistics, and related areas including biostatistics, operations research, and data mining. Each of the two tracks includes 6 courses for a minimum of 24 credits, additional credits are required if the student completes MATH 108 and 109 instead of 113.

(Formerly IDTH 201) This course is for students desiring to satisfy the coverage of STAT 220 ( a full semester of statistics), when less than one full semester of statistics has been taken. Review of inferential statistics; sampling distribution of the sample mean and sample proportion, central limit theorem, confidence intervals and hypothesis tests for one and two means and one and two proportions. Introduction to basic applications: tests of independence, analysis of variance and linear regression. A statistical package must be used as tool. Prerequisite: STAT 206 (IDTH 206) or at least .35 semester, but less than one semester of statistics. Note: Students who receive credit for STAT 201 may not receive credit for STAT 220.

Formerly IDTH 220. Statistics I is composed of an in-depth study of the processes through which statistics are applied in order to learn about environments and events. In this course, there is an intensive focus on the application, analysis, interpretation, and presentation of both descriptive and inferential statistics in myriad contexts. Topics covered include analytical and graphical tools for summarizing categorical and quantitative variables; correlation and simple linear regression; sampling strategies and research design; probability, probability models, and random variables; sampling distribution models; inference for one and two proportions; inference for one and two or more independent means; inference for paired means; inference for comparing counts; and inference for simple linear regression.
Students must enroll in both a lecture section and software-specific laboratory section, in the same academic semester, to successfully complete STAT 220.
This course fulfills the third course in natural Science and Mathematics and Quantitative Reasoning requirement in the core curriculum.
Prerequisites: Math placement at MATH 108 or above; or MATH 100, 101, or 105, 108, 109, 111, or 113. NOTE: Students who receive credit for STAT 220 may not receive credit for STAT 201.

(Formerly IDTH 360) This course introduces students to an advanced statistical software package to effectively apply statistical methods, in general. Students create data sets from raw data files, create variables within a data set, append and/or modify data sets, create subsets, then apply a whole host of statistical procedures, create graphs and produce reports. The course will be based on several leading advanced statistical software packages, which will be chosen from semester to semester to match the needs of the community.
Prerequisites: STAT 220 or STAT 314

Students will work individually with the instructor to identify a statistical research topic of current interest or to identify a real practical problem, for which statistics can be used to produce a feasible solution. State and local governments, companies, businesses, TV channels, or even faculty doing research should be the natural source of real practical problems to be solved. For either the research or the practical problem, the final outcome should be a report with publication potential.

The subject matter of these courses will vary from year to year, but will not duplicate existing courses. Descriptions of these courses are available in the Searchable Class Schedule on Murphy Online, View Searchable Class Schedule